/******************************************************************************
IrstLM: IRST Language Model Toolkit
Copyright (C) 2006 Marcello Federico, ITC-irst Trento, Italy

This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.

This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
Lesser General Public License for more details.

You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301 USA

******************************************************************************/
// Basic Interpolated LM class


#define SHIFT_BETA   1
#define SHIFT_ONE    2
#define SHIFT_ZERO   3
#define SHIFT_ONE_BETA   4
#define LINEAR_WB    5
#define LINEAR_GT    6
#define MIXTURE      7
#define MOD_SHIFT_BETA   8


class interplm:public ngramtable{
	
	int lms;
	
	double epsilon; //Bayes smoothing
	
	int unismooth; //0 Bayes, 1 Witten Bell
	
	int prune_singletons;
	
	int prune_top_singletons;
	
public: 
	
	int backoff; //0 interpolation, 1 Back-off  
	
	interplm(char* ngtfile,int depth=0,TABLETYPE tt=FULL);
	
	int prunesingletons(int flag=-1){
		return (flag==-1?prune_singletons:prune_singletons=flag);
	}
	
	int prunetopsingletons(int flag=-1){
		return (flag==-1?prune_top_singletons:prune_top_singletons=flag);
	}
	
	void gencorrcounts();
	
	void gensuccstat();
	
	virtual int dub(){return dict->dub();}
	
	virtual int dub(int value){ return (dict->dub(value)); }
	
	int setusmooth(int v=0){return unismooth=v;}
	
	double setepsilon(double v=1.0){return epsilon=v;}
	
	ngramtable *unitbl;
	
	void trainunigr();
	
	double unigr(ngram ng);
	
	double zerofreq(int lev);
	
	inline int lmsize(){return lms;}
	
	inline int obswrd(){return dict->size();}
	
	virtual int train(){return 0;}
	
	virtual void adapt(char* /* unused parameter: ngtfile */, double /* unused parameter:  w */){}
	
	virtual double prob(ngram /* unused parameter: ng */,int /* unused parameter: size */){return 0.0;}
	
	virtual double boprob(ngram /* unused parameter: ng */,int /* unused parameter: size */){return 0.0;}
	
	void test_ngt(ngramtable& ngt,int sz=0,int backoff=0,int checkpr=0);
	
	void test_txt(char *filename,int sz=0,int backoff=0,int checkpr=0,char* outpr=NULL);
	
	void test(char* filename,int sz,int backoff=0,int checkpr=0,char* outpr=NULL);
	
	virtual int discount(ngram /* unused parameter: ng */,int /* unused parameter: size */,double& /* unused parameter: fstar */ ,double& /* unused parameter: lambda */,int /* unused parameter: cv*/=0){ return 0;}
	
	virtual int savebin(char* /* unused parameter: filename */,int /* unused parameter: lmsize=2 */){ return 0; }
	
	virtual int netsize(){return 0;}
	
	void lmstat(int level){stat(level);}
	
	virtual ~interplm(){}
	
	
};








